package com.heima.article.job;

import com.alibaba.fastjson.JSON;
import com.heima.article.service.HotArticleService;
import com.heima.common.constants.article.HotArticleConstants;
import com.heima.model.mess.app.ArticleVisitStreamMess;
import com.heima.model.mess.app.UpdateArticleMess;
import com.xxl.job.core.biz.model.ReturnT;
import com.xxl.job.core.handler.annotation.XxlJob;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.dao.DataAccessException;
import org.springframework.data.redis.connection.RedisConnection;
import org.springframework.data.redis.core.ListOperations;
import org.springframework.data.redis.core.RedisCallback;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.data.redis.serializer.RedisSerializer;
import org.springframework.stereotype.Component;
import org.springframework.util.CollectionUtils;

import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.Optional;
import java.util.function.BinaryOperator;
import java.util.stream.Collectors;

@Component
@Slf4j
public class UpdateHotArticleJob {
    @Autowired
    StringRedisTemplate redisTemplate;
    @Autowired
    HotArticleService hotArticleService;

    @XxlJob("updateHotArticleJob")
    public ReturnT updateHotArticleHandler(String params) {
        log.info("热文章分值更新 调度任务开始执行....");
        //1. 获取redis 行为列表中待处理数据
        List<UpdateArticleMess> articleMessList = getUpdateArticleMesses();
        if(CollectionUtils.isEmpty(articleMessList)){
            log.info("热文章分值更新: 太冷清了 未产生任何文章行为 调度任务完成....");
            return ReturnT.SUCCESS;
        }
        //2 将数据按照文章分组 进行聚合统计 得到待更新的数据列表
       List<ArticleVisitStreamMess> waitUpdateScoreData= getArticleVisitStreamMesses(articleMessList);
        if(CollectionUtils.isEmpty(waitUpdateScoreData)){
            log.info("热文章分值更新: 太冷清了 未产生任何文章行为 调度任务完成....");
            return ReturnT.SUCCESS;
        }
        // TODO 定时更新文章热度 更新数据库文章分值
        waitUpdateScoreData.forEach(hotArticleService::updateApArticle);
        log.info("热文章分值更新 调度任务完成....");
        return ReturnT.SUCCESS;
    }

    /**
     * 按照文章文组 每个文章的所有行为 进行聚合处理
     * @param articleMessList 处理结果集合
     * @return
     */
    private List<ArticleVisitStreamMess> getArticleVisitStreamMesses(List<UpdateArticleMess> articleMessList) {
        List<ArticleVisitStreamMess> waitUpdateScoreData=new ArrayList<>();
        //1 按照文章id分组 获取对应分组下的文章列表
        Map<Long, List<UpdateArticleMess>> map = articleMessList.stream()
                .collect(Collectors.groupingBy(UpdateArticleMess::getArticleId));

        //2 计算每个分组的结果
        map.forEach((articleId,messList)->{
            Optional<ArticleVisitStreamMess> reduceResult=
                    messList.stream()
                    .map(articleMes->{
                        ArticleVisitStreamMess visitStreamMess=new ArticleVisitStreamMess();
                        visitStreamMess.setArticleId(articleId);

                        switch (articleMes.getType()){
                            case LIKES:
                                //设置点赞数量
                                visitStreamMess.setLike(articleMes.getAdd());
                                break;
                            case VIEWS:
                                //设置阅读数量
                                visitStreamMess.setView(articleMes.getAdd());
                                break;
                            case COMMENT:
                                //设置评论数量
                                visitStreamMess.setComment(articleMes.getAdd());
                                break;
                            case COLLECTION:
                                //设置收藏数量
                                visitStreamMess.setCollect(articleMes.getAdd());
                                break;


                        }
                        return visitStreamMess;
                    }).reduce(new BinaryOperator<ArticleVisitStreamMess>() {
                        @Override
                        public ArticleVisitStreamMess apply(ArticleVisitStreamMess a1, ArticleVisitStreamMess a2) {
                            a1.setLike(a1.getLike()+a2.getLike());
                            a1.setView(a1.getView()+a2.getView());
                            a1.setComment(a1.getComment()+a2.getComment());
                            a1.setCollect(a1.getCollect()+a2.getCollect());
                            return a1;

                        }
                    });
            if(reduceResult.isPresent()){
                //聚合结果
                ArticleVisitStreamMess visitStreamMess = reduceResult.get();
                log.info("热点文章 聚合计算结果  ===>{}" , visitStreamMess);
                waitUpdateScoreData.add(visitStreamMess);
            }
        });
        return waitUpdateScoreData;
    }

    /**
     * list列表中的待处理行为数据
     *
     * @return
     */
    private List<UpdateArticleMess> getUpdateArticleMesses() {
        // 1. 获取redis 行为列表中待处理数据
        ListOperations listOperations = redisTemplate.opsForList();
        //得到当前行为数据数量
        Long size = listOperations.size(HotArticleConstants.HOT_ARTICLE_SCORE_BEHAVIOR_LIST);
        //采用管道命令 让多个命令保证原子性
        List result = redisTemplate.executePipelined(new RedisCallback<List<UpdateArticleMess>>() {
            @Override
            public List<UpdateArticleMess> doInRedis(RedisConnection connection) throws DataAccessException {
                //开启管道执行命令
                connection.openPipeline();

                //获取 0 到 size-1 的所有集合数据
                connection.lRange(HotArticleConstants.HOT_ARTICLE_SCORE_BEHAVIOR_LIST.getBytes(), 0, (size - 1));

                //截断size 到-1 后续的集合数据
                connection.lTrim(HotArticleConstants.HOT_ARTICLE_SCORE_BEHAVIOR_LIST.getBytes(), size, -1);

                return null;
            }
        }, RedisSerializer.string());

        if (result.size()>0) {
            List<String> listData = (List<String>) result.get(0);
            return listData.stream()
                    .map(str -> JSON.parseObject(str,UpdateArticleMess.class))
                    .collect(Collectors.toList());
        }
        return null;
    }
}